AI Sales Solutions Engineer

Job Description

Champion AI is the strategic future of QAD | Redzone, and we are building a dedicated AI division to own it — this is where the company’s attention, investment, and ambition are concentrated. The strategy and the technical foundation are built; we need solution designers who can execute it and scale it across customers.

There has never been a better moment to sit at the frontier of agentic AI for manufacturing. We are assembling a small team of operators to capture it, and this role helps define what “great” looks like.

The Role

The AI Sales Solutions Engineer is a solution designer. You walk into a customer conversation, understand their end-to-end process, and assemble an agentic solution to fix it — without engineering involvement.

You sit on top of a pre-built foundation — data, semantics, an agent platform, and a library of persona agents. You configure within it; you don’t build it. The platform exposes configuration through natural language and drag-and-drop, so your edge is domain fluency and solution-design instinct, not code.

What You’ll Do

Working hand-in-hand with other Account Executives, you take a qualified opportunity and turn it into a working agentic solution:

• Run process discovery workshops: sit with champion users to map any of the standard enterprise processes (P2P, S2C, O2C, P2M, F2P, R2R) — current state, KPIs, manual effort, bottlenecks, and target state.
• Design the agentic solution: decide which agents, working together, fix the customer’s process — and recognize whether it’s a greenfield build or a brownfield plug-in to an existing system (SAP, Ariba, Coupa, Jaggaer).
• Map KPIs to the platform: confirm the system has the data and the business context to measure what the customer actually cares about.
• Configure each agent: set triggers, decision logic, exceptions, KPIs, data sources, communications, company-specific rules, and hand-offs — all in natural language and drag-and-drop, no code.
• Present the solution: pitch anchored in business outcomes — OTIF, working capital, cycle time, cost reduction — worked backwards to the agents that achieve them.

Qualifications

• You are a quota carrier with 3 or more years of experience selling Tech/AI/SaaS solutions.
• Enterprise domain fluency: operational, end-to-end working knowledge of at least two of P2P, S2C, O2C, P2M, F2P, R2R — not just a consulting view. The deepest value sits in plan-to-make and procure-to-pay.
• Solution-design thinking: ability to decompose a vague business outcome into agents and data flows, and to know when one agent suffices and when several are needed.
• Low-code / natural-language comfort: hands-on with tools like n8n, Zapier, or Make. The agent platform will feel familiar.
• Customer-facing credibility: workshop facilitation and executive-level presentation.

Nice-to-Have

• Background at a major ERP vendor or process consultancy (SAP, Oracle, Coupa, Ariba, or a Big Four firm).
• Hands-on experience with AI tooling.
• Industry depth in manufacturing, particularly tier-one suppliers.

Not Required

Model-building, software-engineering depth, or an ML / data-science background. Engineering owns the platform; you own the solution.

Who Thrives Here

• You are joining a small, entrepreneurial team — not a delivery machine with a ticket queue. We want self-starters who see the opportunity in agentic AI and move without waiting for instructions.
• Self-starter: if a solution pattern or workshop framework doesn’t exist yet, you create it. If a document is missing, you write it.
• Resourceful: you pull in the right people — your AE, Product, and Customer Success — to move a deal forward and get the customer to value.
• Builder’s mindset: you take a strong foundation and a playbook and extend them as the platform matures, rather than waiting for every process to be defined for you.
• If you need rigid structure and a clearly defined process for every situation, this is not the right place. If you want to shape how this role and this division are built, it is.